Average deal size formula and how to calculate it correctly

Average deal size is the total value of the deals in a defined set divided by the number of deals in that same set. The formula is only useful once you decide which deals count, because the result changes a lot if you use closed-won deals, all closed deals, or a narrower segment like new business only.

The average deal size formula in one line

Average deal size = total deal value ÷ number of deals.

The real work is picking the set first. If you want average sales deal size for closed-won deals only, both numbers in the formula must come from closed-won deals only. If you want a broader view of outcomes across the funnel, you can use all closed deals, but then you are no longer measuring realized revenue per win.

For example, if your closed-won deals in a month add up to 60,000 across 4 deals, the average deal size is 15,000.

Which deals count and which ones don't

What belongs in the calculation depends on the question you want answered. Use the same rule for the numerator and denominator, or the number stops meaning much.

Closed-won deals are the cleanest default for revenue reporting. All closed deals can be useful if you are trying to understand the size of outcomes across the funnel, but that is a different question from average deal size. Lost deals usually should not be in a revenue average, because they have no realized value.

If you sell a mix of new business, renewals, and services, set the boundary in advance. A renewal can belong in the calculation if you want a blended customer value metric. It should stay out if you are using average deal size to judge how new business is landing.

This is also where one-off fees need a rule. If setup fees, implementation charges, or similar items are part of the deal you want to measure, include them. If you are trying to track recurring contract value only, keep them out. The important thing is consistency, not one universal answer.

A simple example with real-world messiness

Say you have four closed-won deals in a quarter: one for 5,000, one for 8,000, one for 7,000, and one large deal for 40,000. The total deal value is 60,000, so the average deal size is 15,000.

That average looks healthy, but one large deal is carrying the result. If the 40,000 deal included a 10,000 one-time setup fee, your average changes depending on whether you count that fee as part of deal value. If the 8,000 deal was later refunded by 2,000, a gross booking average and a net revenue average will not match.

Now imagine one of the 7,000 deals was actually a renewal. If renewals are a separate motion in your business, mixing them into the same average can make your new-business pipeline look stronger than it really is.

For example, the same raw deals can produce three different answers:

• Gross bookings average if you include setup fees.
• Net revenue average if you subtract refunds.
• New-business average if you remove renewals and other non-new-logo deals.

That is why the metric needs a written rule, not just a formula.

How average deal size differs from ACV, AOV, and deal value

These terms get mixed up a lot, but they are not the same.

• Average deal size is the average value of the deals in your chosen set.
• ACV usually means average contract value, which is tied to contract terms and often recurring revenue.
• AOV means average order value, which is more common in ecommerce or transaction-based sales.
• Deal value is the value of one specific deal, not an average.

They can point in the same direction, but they answer different questions. If you are looking at recurring contracts, ACV may be the better label. If you are looking at individual sales transactions, average deal size may be the cleaner term. If you are looking at one signed opportunity, that is deal value, not average deal size.

The easiest mistake is to use ACV when you really mean average deal size, or to average a mix of contract lengths and call it ACV. If your contracts vary a lot, make sure the label matches the math.

How to calculate it in a spreadsheet or CRM

1. Filter to the deal set you actually want, such as closed-won deals in Q4.
2. Sum the correct value field, such as net deal value or booked revenue.
3. Count the same filtered deals.
4. Divide the sum by the count.

In Excel or Google Sheets, that often looks like SUMIFS for the value field and COUNTIFS for the deal count, using the same filters for stage, date range, segment, and deal type. If your CRM has a report builder, set the report to the same filters and use the average or formula field only after confirming which revenue field the CRM is using.

A simple spreadsheet setup is usually enough:

• Column A: deal ID
• Column B: stage
• Column C: close date
• Column D: segment
• Column E: net deal value
• Column F: deal type

Then apply the same filters to both the sum and the count. If the filters do not match, the result is wrong even if the arithmetic is fine.

A common spreadsheet mistake is to sum all revenue rows but count only closed-won deals, or to include lost opportunities in the count because they are still sitting in the export. Another common one is double-counting renewal records or setup fees that appear as separate line items.

If your CRM rolls line items into one opportunity, check whether the total is stored at the deal level or the product level. If it is stored per line item, you may need to aggregate first before you calculate the average.

How to read the number without fooling yourself

Average deal size is useful, but it can mislead you if a few large deals or odd one-offs sit in the data. When the distribution is lopsided, median deal size often tells a truer story than one overall average. Segmented averages are also better when you sell very different deal types, such as new business versus renewals, or software-only deals versus deals with implementation fees.

Use monthly averages when you need a quick operational pulse, but expect more noise. Quarterly averages are usually steadier for small teams, and yearly averages are better when deal volume is low or seasonality is strong. The key is to keep the time window consistent so the metric means the same thing each time you look at it.

For forecasting, treat average deal size as one input, not a promise. If your future mix shifts toward smaller deals, the old average will overstate revenue. If you set targets from one inflated average that includes a few outliers, you can end up overcommitting the team. I would use the average for planning, then check it against the median and against segment-level averages before I trust it.

The safest habit is to pair the average with median deal size, segmented averages, and a clear rule for closed-won versus all closed deals.

Where the metric stops being useful

Average deal size does not work well when the group you are measuring is too mixed. If enterprise deals, self-serve deals, renewals, and services all sit in the same bucket, the average can hide more than it shows.

It also stops being a clean metric if you use it to describe open pipeline. Open opportunities are forecasts, not completed deals, so they belong in a pipeline value report, not in a deal size average.

If you need one number for leadership, use the average only when the deal mix is stable enough to make it meaningful. If the mix changes from month to month, the average can be technically correct and still not useful.